Overview

Dataset statistics

Number of variables9
Number of observations40
Missing cells1
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory81.3 B

Variable types

Categorical5
Numeric4

Dataset

Description과세액 중 비과세액과 감면액이 차지하는 비율 현황 제공 (시도명 시군구명 자치단체코드 세목명 과세년도 비과세금액 감면금액 부과금 비과세감면율)
URLhttps://www.data.go.kr/data/15078337/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
비과세금액 is highly overall correlated with 감면금액 and 1 other fieldsHigh correlation
감면금액 is highly overall correlated with 비과세금액 and 3 other fieldsHigh correlation
부과금액 is highly overall correlated with 감면금액 and 1 other fieldsHigh correlation
비과세감면율 is highly overall correlated with 비과세금액 and 2 other fieldsHigh correlation
세목명 is highly overall correlated with 감면금액 and 2 other fieldsHigh correlation
비과세금액 has 1 (2.5%) missing valuesMissing
감면금액 has unique valuesUnique
비과세금액 has 9 (22.5%) zerosZeros
감면금액 has 1 (2.5%) zerosZeros
부과금액 has 5 (12.5%) zerosZeros
비과세감면율 has 5 (12.5%) zerosZeros

Reproduction

Analysis started2023-12-12 19:11:04.365497
Analysis finished2023-12-12 19:11:06.671062
Duration2.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
경상북도
40 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경상북도
2nd row경상북도
3rd row경상북도
4th row경상북도
5th row경상북도

Common Values

ValueCountFrequency (%)
경상북도 40
100.0%

Length

2023-12-13T04:11:06.741518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:11:06.851870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상북도 40
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
봉화군
40 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row봉화군
2nd row봉화군
3rd row봉화군
4th row봉화군
5th row봉화군

Common Values

ValueCountFrequency (%)
봉화군 40
100.0%

Length

2023-12-13T04:11:06.979150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:11:07.104077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
봉화군 40
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
47920
40 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row47920
2nd row47920
3rd row47920
4th row47920
5th row47920

Common Values

ValueCountFrequency (%)
47920 40
100.0%

Length

2023-12-13T04:11:07.237173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:11:07.363152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
47920 40
100.0%

세목명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
교육세
5 
등록세
5 
재산세
5 
주민세
5 
취득세
5 
Other values (3)
15 

Length

Max length7
Median length3
Mean length3.875
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row교육세
2nd row등록세
3rd row재산세
4th row주민세
5th row취득세

Common Values

ValueCountFrequency (%)
교육세 5
12.5%
등록세 5
12.5%
재산세 5
12.5%
주민세 5
12.5%
취득세 5
12.5%
자동차세 5
12.5%
등록면허세 5
12.5%
지역자원시설세 5
12.5%

Length

2023-12-13T04:11:07.485554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:11:07.634088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
교육세 5
12.5%
등록세 5
12.5%
재산세 5
12.5%
주민세 5
12.5%
취득세 5
12.5%
자동차세 5
12.5%
등록면허세 5
12.5%
지역자원시설세 5
12.5%

과세년도
Categorical

Distinct5
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2017
8 
2018
8 
2019
8 
2020
8 
2021
8 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017
2nd row2017
3rd row2017
4th row2017
5th row2017

Common Values

ValueCountFrequency (%)
2017 8
20.0%
2018 8
20.0%
2019 8
20.0%
2020 8
20.0%
2021 8
20.0%

Length

2023-12-13T04:11:07.789329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:11:07.908664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 8
20.0%
2018 8
20.0%
2019 8
20.0%
2020 8
20.0%
2021 8
20.0%

비과세금액
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct31
Distinct (%)79.5%
Missing1
Missing (%)2.5%
Infinite0
Infinite (%)0.0%
Mean4.2301741 × 108
Minimum0
Maximum2.327311 × 109
Zeros9
Zeros (%)22.5%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-13T04:11:08.038815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12369500
median17611000
Q34.323835 × 108
95-th percentile2.1183803 × 109
Maximum2.327311 × 109
Range2.327311 × 109
Interquartile range (IQR)4.30014 × 108

Descriptive statistics

Standard deviation7.5536163 × 108
Coefficient of variation (CV)1.7856514
Kurtosis1.2879265
Mean4.2301741 × 108
Median Absolute Deviation (MAD)17611000
Skewness1.6685663
Sum1.6497679 × 1010
Variance5.705712 × 1017
MonotonicityNot monotonic
2023-12-13T04:11:08.479063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 9
22.5%
1751504000 1
 
2.5%
90874000 1
 
2.5%
2434000 1
 
2.5%
16361000 1
 
2.5%
2319632000 1
 
2.5%
33455000 1
 
2.5%
2327311000 1
 
2.5%
79421000 1
 
2.5%
3380000 1
 
2.5%
Other values (21) 21
52.5%
ValueCountFrequency (%)
0 9
22.5%
2305000 1
 
2.5%
2434000 1
 
2.5%
2689000 1
 
2.5%
2896000 1
 
2.5%
3380000 1
 
2.5%
13620000 1
 
2.5%
15547000 1
 
2.5%
15697000 1
 
2.5%
16361000 1
 
2.5%
ValueCountFrequency (%)
2327311000 1
2.5%
2319632000 1
2.5%
2096019000 1
2.5%
1969577000 1
2.5%
1860275000 1
2.5%
1751504000 1
2.5%
956806000 1
2.5%
867123000 1
2.5%
866992000 1
2.5%
773893000 1
2.5%

감면금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE  ZEROS 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3901402 × 108
Minimum0
Maximum1.455028 × 109
Zeros1
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-13T04:11:08.626007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile567650
Q17597750
median86449500
Q31.8626425 × 108
95-th percentile1.2776558 × 109
Maximum1.455028 × 109
Range1.455028 × 109
Interquartile range (IQR)1.786665 × 108

Descriptive statistics

Standard deviation4.2681664 × 108
Coefficient of variation (CV)1.7857389
Kurtosis3.2933095
Mean2.3901402 × 108
Median Absolute Deviation (MAD)83621000
Skewness2.1761356
Sum9.560561 × 109
Variance1.8217244 × 1017
MonotonicityNot monotonic
2023-12-13T04:11:08.773878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
588000 1
 
2.5%
139398000 1
 
2.5%
13406000 1
 
2.5%
1672000 1
 
2.5%
0 1
 
2.5%
210005000 1
 
2.5%
455589000 1
 
2.5%
1257500000 1
 
2.5%
132617000 1
 
2.5%
74944000 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
0 1
2.5%
181000 1
2.5%
588000 1
2.5%
1672000 1
2.5%
1848000 1
2.5%
2084000 1
2.5%
2259000 1
2.5%
2287000 1
2.5%
3370000 1
2.5%
3613000 1
2.5%
ValueCountFrequency (%)
1455028000 1
2.5%
1401513000 1
2.5%
1271137000 1
2.5%
1257500000 1
2.5%
1232514000 1
2.5%
455589000 1
2.5%
218569000 1
2.5%
214680000 1
2.5%
210005000 1
2.5%
194080000 1
2.5%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct36
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0187535 × 109
Minimum0
Maximum7.074396 × 109
Zeros5
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-13T04:11:08.904470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.30143 × 108
median1.1394115 × 109
Q32.7446072 × 109
95-th percentile6.4716092 × 109
Maximum7.074396 × 109
Range7.074396 × 109
Interquartile range (IQR)2.3144642 × 109

Descriptive statistics

Standard deviation2.1129932 × 109
Coefficient of variation (CV)1.0466822
Kurtosis0.16071573
Mean2.0187535 × 109
Median Absolute Deviation (MAD)1.0615805 × 109
Skewness1.121353
Sum8.0750139 × 1010
Variance4.4647404 × 1018
MonotonicityNot monotonic
2023-12-13T04:11:09.026452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0 5
 
12.5%
712030000 1
 
2.5%
590836000 1
 
2.5%
307145000 1
 
2.5%
2360569000 1
 
2.5%
1914456000 1
 
2.5%
466225000 1
 
2.5%
6461509000 1
 
2.5%
4625571000 1
 
2.5%
2320079000 1
 
2.5%
Other values (26) 26
65.0%
ValueCountFrequency (%)
0 5
12.5%
276852000 1
 
2.5%
290234000 1
 
2.5%
302775000 1
 
2.5%
307145000 1
 
2.5%
321897000 1
 
2.5%
466225000 1
 
2.5%
536950000 1
 
2.5%
553782000 1
 
2.5%
590836000 1
 
2.5%
ValueCountFrequency (%)
7074396000 1
2.5%
6663514000 1
2.5%
6461509000 1
2.5%
6218629000 1
2.5%
5717094000 1
2.5%
4625571000 1
2.5%
4338995000 1
2.5%
3839116000 1
2.5%
3721041000 1
2.5%
3415360000 1
2.5%

비과세감면율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct35
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.4815
Minimum0
Maximum125.15
Zeros5
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-13T04:11:09.183824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.445
median13.905
Q334.6475
95-th percentile120.4505
Maximum125.15
Range125.15
Interquartile range (IQR)32.2025

Descriptive statistics

Standard deviation39.905324
Coefficient of variation (CV)1.3091654
Kurtosis1.1740001
Mean30.4815
Median Absolute Deviation (MAD)13.905
Skewness1.556687
Sum1219.26
Variance1592.4349
MonotonicityNot monotonic
2023-12-13T04:11:09.340178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0.0 5
 
12.5%
0.09 2
 
5.0%
3.23 1
 
2.5%
13.8 1
 
2.5%
29.7 1
 
2.5%
0.07 1
 
2.5%
120.45 1
 
2.5%
105.18 1
 
2.5%
31.44 1
 
2.5%
0.03 1
 
2.5%
Other values (25) 25
62.5%
ValueCountFrequency (%)
0.0 5
12.5%
0.03 1
 
2.5%
0.07 1
 
2.5%
0.08 1
 
2.5%
0.09 2
 
5.0%
3.23 1
 
2.5%
3.3 1
 
2.5%
3.48 1
 
2.5%
4.16 1
 
2.5%
4.31 1
 
2.5%
ValueCountFrequency (%)
125.15 1
2.5%
120.46 1
2.5%
120.45 1
2.5%
119.68 1
2.5%
117.2 1
2.5%
105.18 1
2.5%
50.21 1
2.5%
37.4 1
2.5%
37.34 1
2.5%
35.39 1
2.5%

Interactions

2023-12-13T04:11:05.972034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:11:04.622562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:11:05.048398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:11:05.513035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:11:06.084682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:11:04.746217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:11:05.139167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:11:05.602382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:11:06.208070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:11:04.844700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:11:05.279205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:11:05.720384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:11:06.317422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:11:04.954099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:11:05.404634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:11:05.834026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:11:09.446160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세년도비과세금액감면금액부과금액비과세감면율
세목명1.0000.0000.6680.7600.8600.849
과세년도0.0001.0000.0000.0000.0000.000
비과세금액0.6680.0001.0000.7350.7710.833
감면금액0.7600.0000.7351.0000.7310.817
부과금액0.8600.0000.7710.7311.0000.683
비과세감면율0.8490.0000.8330.8170.6831.000
2023-12-13T04:11:09.556524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세년도세목명
과세년도1.0000.000
세목명0.0001.000
2023-12-13T04:11:09.641341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
비과세금액감면금액부과금액비과세감면율세목명과세년도
비과세금액1.0000.7550.2990.8980.4330.000
감면금액0.7551.0000.5460.7910.5730.000
부과금액0.2990.5461.0000.2330.6390.000
비과세감면율0.8980.7910.2331.0000.6620.000
세목명0.4330.5730.6390.6621.0000.000
과세년도0.0000.0000.0000.0000.0001.000

Missing values

2023-12-13T04:11:06.463619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:11:06.616925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율
0경상북도봉화군47920교육세2017058800023200790000.03
1경상북도봉화군47920등록세20170337000000.0
2경상북도봉화군47920재산세201717515040001836590001546270000125.15
3경상북도봉화군47920주민세201770545000892600061790600012.86
4경상북도봉화군47920취득세20179568060001401513000666351400035.39
5경상북도봉화군47920자동차세20171761100014773900038391160004.31
6경상북도봉화군47920등록면허세2017289600012154400055378200022.47
7경상북도봉화군47920지역자원시설세2017696380001775900027685200031.57
8경상북도봉화군47920교육세20180184800022779940000.08
9경상북도봉화군47920등록세20180361300000.0
시도명시군구명자치단체코드세목명과세년도비과세금액감면금액부과금액비과세감면율
30경상북도봉화군47920등록면허세202033800007494400071203000011.0
31경상북도봉화군47920지역자원시설세2020794210001660500030277500031.72
32경상북도봉화군47920교육세20210225900025210230000.09
33경상북도봉화군47920등록세2021<NA>228700000.0
34경상북도봉화군47920재산세202123273110002146800002123990000119.68
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